{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Day16 进阶构图元素——文字\n",
    "\n",
    "　　文字是我们创作数据可视化作品非常重要的修饰元素，可用于标注数据记录或添加说明文字，今天我们就来学习如何在`matplotlib`中添加文字。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T09:01:02.543610Z",
     "iopub.status.busy": "2020-11-03T09:01:02.543610Z",
     "iopub.status.idle": "2020-11-03T09:01:02.818909Z",
     "shell.execute_reply": "2020-11-03T09:01:02.818909Z",
     "shell.execute_reply.started": "2020-11-03T09:01:02.543610Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "matplotlib版本： 3.3.2\n"
     ]
    }
   ],
   "source": [
    "import matplotlib;print('matplotlib版本：', matplotlib.__version__)\n",
    "import matplotlib.pyplot as plt # 从matplotlib中导入我们最经常使用的pyplot子模\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei'] # 设定默认字体为SimHei以解决中文显示乱码问题\n",
    "plt.rcParams['axes.unicode_minus'] = False # 解决图像负号'-'不正常显示的问题"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　我们在`matplotlib`中添加文字最常用的方式是通过`text()`，就像下面这个非常基础的例子一样："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T09:01:02.819871Z",
     "iopub.status.busy": "2020-11-03T09:01:02.819871Z",
     "iopub.status.idle": "2020-11-03T09:01:02.969471Z",
     "shell.execute_reply": "2020-11-03T09:01:02.969471Z",
     "shell.execute_reply.started": "2020-11-03T09:01:02.819871Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.font_manager as fm # 用于导入自定义字体\n",
    "\n",
    "x = np.array(range(5))\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(x, x)\n",
    "\n",
    "# 添加文字用到的最基础的几个参数\n",
    "ax.text(x=2, # 文字锚点的x坐标\n",
    "        y=2, # 文字锚点的y坐标\n",
    "        s='测试', # 文字内容\n",
    "        fontsize=30, # 文字像素大小\n",
    "       );"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　除了上述的基础参数之外，`matplotlib`中的`text()`还拥有很多实用的参数："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T09:01:02.970469Z",
     "iopub.status.busy": "2020-11-03T09:01:02.970469Z",
     "iopub.status.idle": "2020-11-03T09:01:03.098128Z",
     "shell.execute_reply": "2020-11-03T09:01:03.097130Z",
     "shell.execute_reply.started": "2020-11-03T09:01:02.970469Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(x, x)\n",
    "\n",
    "# 以及有关字体的一些比较好理解的基本参数\n",
    "ax.text(x=2, \n",
    "        y=2, \n",
    "        s='测试',\n",
    "        fontsize=30,\n",
    "        alpha=0.8, # 控制文字的透明度\n",
    "        backgroundcolor='lightgrey', # 设置文字部分的背景填充色\n",
    "        color='red', # 设置文字颜色\n",
    "        rotation=90, # 设置文字逆时针旋转角度\n",
    "       );"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　而除了上述基础参数之外，`text()`还拥有一些比较有意思的特殊参数："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T09:01:03.099124Z",
     "iopub.status.busy": "2020-11-03T09:01:03.099124Z",
     "iopub.status.idle": "2020-11-03T09:01:03.237752Z",
     "shell.execute_reply": "2020-11-03T09:01:03.237752Z",
     "shell.execute_reply.started": "2020-11-03T09:01:03.099124Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(x, x)\n",
    "\n",
    "ax.text(x=2, \n",
    "        y=2, \n",
    "        s='测试',\n",
    "        fontsize=30,\n",
    "        ha='center', # 设置文字水平居中于锚点\n",
    "        va='center' # 设置文字竖直居中于锚点\n",
    "       );"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T09:01:03.238750Z",
     "iopub.status.busy": "2020-11-03T09:01:03.238750Z",
     "iopub.status.idle": "2020-11-03T09:01:03.355439Z",
     "shell.execute_reply": "2020-11-03T09:01:03.355439Z",
     "shell.execute_reply.started": "2020-11-03T09:01:03.238750Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(x, x)\n",
    "\n",
    "ax.text(x=2, \n",
    "        y=2, \n",
    "        s='测试\\n测试测试测试\\n测试测试',\n",
    "        fontsize=30,\n",
    "        # 设置多行文字（即字符串内包含\\n换行）的整体对齐方式\n",
    "        # 有left、center以及right三种选项\n",
    "        ma='center' \n",
    "       );"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T09:01:03.357432Z",
     "iopub.status.busy": "2020-11-03T09:01:03.357432Z",
     "iopub.status.idle": "2020-11-03T09:01:03.651646Z",
     "shell.execute_reply": "2020-11-03T09:01:03.651646Z",
     "shell.execute_reply.started": "2020-11-03T09:01:03.357432Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(x, x)\n",
    "\n",
    "# 文字内容可传入由$包围的字符串从而书写公式\n",
    "ax.text(x=2, \n",
    "        y=2, \n",
    "        s='$y=ax+b$',\n",
    "        fontsize=30\n",
    "       );"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　默认情况下，我们传入`text()`的x与y参数是与坐标轴x与y的范围相对应的，若想在x和y方向上基于0-1的比例来定位文字，可添加参数`transform=ax.transAxes`："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T09:01:03.652642Z",
     "iopub.status.busy": "2020-11-03T09:01:03.652642Z",
     "iopub.status.idle": "2020-11-03T09:01:03.790275Z",
     "shell.execute_reply": "2020-11-03T09:01:03.790275Z",
     "shell.execute_reply.started": "2020-11-03T09:01:03.652642Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(x, x)\n",
    "\n",
    "ax.text(x=1, \n",
    "        y=1, \n",
    "        s='测试',\n",
    "        fontsize=30,\n",
    "        transform=ax.transAxes\n",
    "       );"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　而如果想要使用外部自定义字体，可以配合`matplotlib`中的`font_manager`，按照下面的方式来传入外部字体文件（ttf文件）："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T09:01:03.791302Z",
     "iopub.status.busy": "2020-11-03T09:01:03.791302Z",
     "iopub.status.idle": "2020-11-03T09:01:03.887050Z",
     "shell.execute_reply": "2020-11-03T09:01:03.887050Z",
     "shell.execute_reply.started": "2020-11-03T09:01:03.791302Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.font_manager as fm\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(5, 5))\n",
    "\n",
    "ax.text(0.5, 0.5, '柳暗花明又一村', fontsize=40, va='center', ha='center', \n",
    "        fontproperties=fm.FontProperties(fname=\"fonts/汉仪秀英体简.ttf\"),\n",
    "        transform=ax.transAxes);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 课后测验：\n",
    "\n",
    "　　接下来的时间交给你们，还记得开头的示例图片吗，我用`matplotlib`仿了一个版本如下图所示：\n",
    "\n",
    "<center>\n",
    "    <img src='imgs/课后题目.png' width=650>\n",
    "    </img>\n",
    "</center>\n",
    "  \n",
    "　　请在下面代码的基础上，从`fonts`文件夹下挑选出适合的字体，尽量还原上图。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T09:01:03.888014Z",
     "iopub.status.busy": "2020-11-03T09:01:03.888014Z",
     "iopub.status.idle": "2020-11-03T09:01:03.893001Z",
     "shell.execute_reply": "2020-11-03T09:01:03.892003Z",
     "shell.execute_reply.started": "2020-11-03T09:01:03.888014Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 6))\n",
    "\n",
    "s1 = '他强由他强，'\n",
    "s2 = '清风拂山岗；'\n",
    "s3 = '他横由他横，'\n",
    "s4 = '明月照大江；'\n",
    "s5 = '他自狠来他自恶，'\n",
    "s6 = '我自一口真气足。'\n",
    "\n",
    "'''补上你的代码'''\n",
    "\n",
    "\n",
    "for i,str in enumerate([s1,s2,s3,s4,s5,s6]):\n",
    "    ax.text(0.25+0.1*i,1,s='\\n'.join(list(str)),fontsize=40,\n",
    "        va='top',\n",
    "       fontproperties=fm.FontProperties(fname=\"fonts/FZZJ-HLYHXSJW.TTF\"),\n",
    "       transform=ax.transAxes);\n",
    "\n",
    "ax.set_facecolor('#fef4b4')\n",
    "fig.set_facecolor('#fef4b4')\n",
    "\n",
    "ax.axis('off')\n",
    "\n",
    "fig.savefig('课后题目.png', dpi=500, pad_inches=0.2, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 请在今天对应的帖子下回复补充过注释的代码截图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, '他强由他强，'),\n",
       " (1, '清风拂山岗；'),\n",
       " (2, '他横由他横，'),\n",
       " (3, '明月照大江；'),\n",
       " (4, '他自狠来他自恶，'),\n",
       " (5, '我自一口真气足。')]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(enumerate([s1,s2,s3,s4,s5,s6]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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